« La petite mer d’Enghien » : un site pour une villégiature parisienne
Bibliographic record
Abstract
À la fois lac d’Elvire, lac Majeur, lac de Genève, terre chérie de l’auteur de l’Émile, l’un des plus jolis pays du monde, véritable miniature des grands lacs suisses, petite mer... Quel est ce lieu chanté par les plus belles plumes ? Alfred de Musset, Théodore de Banville, Hector Malot, Alphonse Daudet, Guy de Maupassant, Alexandre Dumas, les frères Goncourt ont connu et évoqué le site, de même que nombre de romanciers oubliés. Thème décliné en poésie, en musique, référence géographique associée à Pékin, au Canada, en passant par la Sibérie occidentale... Enghien-les-Bains doit sans doute cette notoriété à sa proximité avec la capitale. Station thermale, mais également lieu de villégiature au bord d’un lac, elle a suscité bien des exercices littéraires où la surenchère de références, la métaphore et l’emphase promeuvent le site. Expérience urbaine d’avant-garde, colonie au dessin empruntant aux modèles anglais, tentative de réponse architecturale à la présence du lac, Enghien mérite une attention particulière.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.011 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".